Portucalense University (PORTUGAL)
About this paper:
Appears in: ICERI2020 Proceedings
Publication year: 2020
Pages: 9062-9071
ISBN: 978-84-09-24232-0
ISSN: 2340-1095
doi: 10.21125/iceri.2020.2015
Conference name: 13th annual International Conference of Education, Research and Innovation
Dates: 9-10 November, 2020
Location: Online Conference
The trend of massification seen in recent years in Higher Education (HE) in Portugal has provided access to groups of students very different socio-culturally from each other, with a greater presence of non-traditional students, that is, worker-students, International students, students from professional and technological specialization courses and special regimes (e.g. Higher than 23 years).

Associated with the diversity of students who access HE, the question arises of their academic skills and motivations, since the instituted numerus clausus system favors the increase in the percentage of students not placed in first option “course-institution” pairs. On the other hand, the implementation of quality assurance systems in Higher Education Institutions (HEIs) and the increased requirements for accreditation of courses and research centers lead HEIs to be increasingly concerned with issues related to improving teaching-learning and training efficiency.

HEIs therefore need instruments that allow them to better understand who their natural candidates are and what factors influence the academic success rate of students enrolled in their courses. With this information available, they will be able to act more precisely in the specific and more personalized follow-up of groups of students with characteristics of identified education path/academic results, as well as optimize their resources in the training offer and consequently in attracting students.

The work reported in this paper aims to analyze, using a Business Intelligence (BI) system, the characteristics of students enrolled in the various courses of a Portuguese HEI, and to determine the influence of several factors on students' academic success. These factors include data related to students’ academic background prior to entering HE and sociodemographic data that will be crossed with information regarding students' performance along and in the completion of the HEI enrollment course.

For this purpose, a sample of students enrolled in 1st cycle courses of the HEI between 2011 to 2019 was used, considering the following variables for the analysis: secondary school attended, admission regime and grade, gender, age, region of provenance, educational level and parents’ professional situation. These data were previously anonymized and correlated with data related to the students' performance during the course and employment situation at the end of the course. The QlikSense BI tool was used and the analysis of indicators and correlations carried out were made available through a performance monitoring system.

The contribution of this work is two-fold. On the one hand, the study of the indicators and segmentation of students carried out within the scope of this project may serve as a basis for a better knowledge of the profiles of students of the target HEI and an understanding of the factors that influence the academic and professional success of students. With the knowledge obtained, the HEI will be able to more easily design a differentiating strategy for the enrolled students, taking into account their respective profiles and evidenced needs, improving the training offer and creating opportunities at curricular and extracurricular level, as well as providing adapted tutoring projects to the various groups. On the other hand, the training efficiency indicators and correlations identified may serve as a basis for other projects and initiatives to analyze the performance of students in HE.
Higher Education, Students performance analysis, Business Intelligence.